Efficient Techniques for Directed Test Generation Using Incremental Satisfiability

P. Mishra, Mingsong Chen
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引用次数: 19

Abstract

Functional validation is a major bottleneck in the current SOC design methodology. While specification-based validation techniques have proposed several promising ideas, the time and resources required for directed test generation can be prohibitively large. This paper presents an efficient test generation methodology using incremental satisfiability. The existing researches have used incremental SAT to improve counterexample (test) generation involving only one property with different bounds. This paper is the first attempt to utilize incremental satisfiability in directed test generation involving multiple properties. The contribution of this paper is a novel methodology to share learning across multiple properties by developing efficient techniques for property clustering, name substitution, and selective forwarding of conflict clauses. Our experimental results using both software and hardware benchmarks demonstrate that our approach can drastically (on average four times) reduce the overall test generation time.
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利用增量可满足性生成定向测试的有效技术
功能验证是当前SOC设计方法的主要瓶颈。虽然基于规范的验证技术已经提出了一些很有前途的想法,但是直接测试生成所需的时间和资源可能非常多。本文提出了一种利用增量可满足性的有效测试生成方法。现有的研究使用增量SAT来改进只涉及一个不同界的性质的反例(测试)生成。本文首次尝试将增量可满足性应用于多属性定向测试生成中。本文的贡献是通过开发高效的属性聚类、名称替换和冲突子句的选择性转发技术,提供了一种跨多个属性共享学习的新方法。我们使用软件和硬件基准测试的实验结果表明,我们的方法可以显著地(平均四倍)减少总体测试生成时间。
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